Four PhD positions in the European Training Network FORA: Fog Computing for Robotics and Industrial Automation DTU Compute Denmark

Four PhD positions in the European Training Network FORA: Fog Computing for Robotics and Industrial Automation


DTU Compute

Deadline 1 October 2017

You can apply for the job at DTU Compute by completing the following application form.


Apply online


DTU Compute’s Sections for Embedded Systems Engineering (ESE), would like to invite applications for four 3-year PhD positions in the European Training Network for Fog Computing for Robotics and Industrial Automation (FORA). The FORA project is founded by the European Union’s Horizon 2020 research and innovation programme. The PhD students are expected to start between Nov. 1st, 2017 and April 1st, 2018. We prefer to fill the positions before the end of 2017.

Our department DTU Compute is an internationally unique academic environment spanning the science disciplines mathematics, statistics and computer science. At the same time we are an engineering department covering informatics and communication technologies (ICT) in their broadest sense. Finally, we play a major role in addressing the societal challenges of the digital society where ICT is a part of every industry, service, and human endeavour.

DTU Compute strives to achieve research excellence in its basic science disciplines, to achieve technological leadership in research and innovation, and to address societal challenges in collaboration with partners at DTU and other academic institutions, nationally and internationally, and, equally important, with industry and organizations. We communicate and collaborate with leading centres and strategic partners in order to increase participation in major consortia.

DTU Compute plays a central role in education at all levels of the engineering programmes at DTU—both in terms of our scientific disciplines and our didactic innovation. 

Project Description

We are at the beginning of a new industrial revolution, Industry 4.0, which will only become a reality through the convergence of Operational and Information Technologies (OT & IT), and this convergence will be achieved through Fog Computing.   

FORA is an interdisciplinary, international, intersectoral network that will train the next generation of researchers in Fog Computing with applicability to industrial automation. FORA’s researchers will receive integrated training across key areas (computer science and engineering, control engineering and industrial automation, data science) necessary to fully realize the potential of Fog Computing for Industry 4.0 and will move between academic and industrial environments to promote interdisciplinary and intersectoral learning. Please visit the FORA website to learn more about these positions.

We are looking for PhD students to perform research on the following PhD projects.

PhD Project 1: Open source Fog Node: hardware support for virtualization 

  • Main supervisor: Prof. Martin Schoeberl, (contact person)
  • Co-supervisor: Prof. Jens Sparsø,



  • Develop and evaluate time-predictable hardware mechanisms to support virtualization, such as time-predictable virtual memory and time-predictable virtualization of I/O
  • Develop an open source implementation of a Fog Node hardware, with these virtualization mechanisms


Expected Results: 

  • Open-source prototype implementation of a Fog Node (FN) hardware, extending the T-CREST platform based on PATMOS processors
  • Time-predictable virtualization of I/O devices and services
  • Physical virtualization through manycore processors power down and up
  • Segment based memory protection with time-predictable address translation
  • Cache partitioning to remove cache related preemption delays
  • Integration and evaluation of these hardware support mechanisms into PikeOS.


Please find out more details here.   

PhD Project 2: Fog configuration for critical control applications 

  • Main supervisor: Prof. Paul Pop, (contact person)
  • Co-supervisor: Prof, Jan Madsen,



  • Support the virtualisation of control needed for the IT/OT convergence
  • Develop methods and tools for the configuration of the Fog Computing Platform for critical control applications, such that they have the same level of service as on a dedicated OT infrastructure.


Expected Results: 

  • Evaluation and analysis report of the mechanisms introducing latencies and jitter that increase the worst-case delays in the network, and decrease the dependability
  • Methods and tools for the configuration of Fog Nodes and for the configuration of TSN switches
  • Analysis and optimization algorithms to maximise the QoC
  • Evaluation and integration of the methods and tools with TTTech’s tool flows.


Please find out more details here.   

PhD Project 3: Fog Computing Security 

  • Main supervisor: Associate Prof. Nicola Dragoni, (contact person) 



  • Analyze the security threats of the Fog Computing infrastructure for Industry 4.0 using use cases from the industrial partners.
  • Develop a security framework that takes advantage of the Fog Nodes (FNs) and Time-Sensitive Networking (TSN) as security-enabling devices for the system.


Expected Results: 

  • Elicitation and definition of attacker models and attack scenarios for industrial automation when using Fog Computing.
  • Propose security services that can be offered by Fog Nodes to mitigate the identified security threats, without jeopardizing the operations and safety of the industrial applications.
  • Develop and implement selected security services in the FNs, showcasing online reconfiguration methods to prevent and recover from attacks.
  • Design and implement algorithms for anomaly detection, which use of the available access to data streams to detect attacks.


Please find out more details here.   

PhD Project 4: Distributed real-time operational data analytics 

  • Main-supervisor: Prof. Jan Larsen (contact person)
  • Co-supervisor: Prof. Lars Kai Hansen,



  • Propose data analytics for Industry 4.0 that exploit the connectivity and data access features of the Fog Nodes.
  • Implement a distributed real-time data analytics solution based on Machine-Learning-as-a-Service.
  • Demonstrate the data analytics solution on an industrial use case.


Expected Results: 

  • Distributed data representation and modeling, using the services provided by the Fog Nodes, which are close to the machines (robots, actuators, sensors).
  • Distributed real-time machine learning algorithms that use the Fog Computing Platform.
  • Implementation of the ML algorithms using ML-as-a-Service microservices.
  • Evaluation of the approaches, and quantification of value gains obtained from the improved operations.


Please find out more details here.  


  • Candidates shall, at the time of recruitment by DTU, be in the first four years (full-time equivalent research experience) of their research careers and not yet have been awarded a doctoral degree.
  • At the time of recruitment by DTU, candidates must not have resided or carried out their main activity (work, studies, etc.) in Denmark for more than 12 months in the 3 years immediately prior to the reference date. Compulsory national service and/or short stays such as holidays are not taken into account. More details about this “mobility rule” mandatory in an European Training Network are here.
  • Candidates must have a master degree in computer science, applied mathematics, or engineering, or equivalent academic qualifications.
  • Please see the detailed pages of each PhD project and contact the main supervisors for additional requirements.
  • Furthermore, good command of the English language is essential, and demonstrated ability to write technical reports or scientific articles is a plus.
Approval and Enrolment 

The scholarship for the PhD degree is subject to academic approval, and the candidate will be enrolled in the DTU Compute PhD School Programme. For information about the general requirements for enrolment and the general planning of the scholarship studies, please see the DTU PhD Guide.

We offer

We offer an interesting and challenging job in an international environment focusing on education, research, scientific advice and innovation, which contribute to enhancing the economy and improving social welfare. We strive for academic excellence, collegial respect and freedom tempered by responsibility. The Technical University of Denmark (DTU) is a leading technical university in northern Europe and benchmarks with the best universities in the world.

Salary and appointment terms 

The salary and appointment terms are consistent with the current rules for PhD degree students. The period of employment is 3 years.

Further Information

Further information concerning the project can be obtained from FORA website information concerning the application is available at the DTU Compute PhD homepage or by contacting PhD coordinator Lene Matthisson +45 4525 3377.


Applications must be submitted in English as one single PDF, and we must have your online application by 1 October 2017. Please open the link in the red bar in the top of the page: "apply online" (“ansøg online”).

In the field “Please indicate which position(s) you would like to apply for” please indicate which project you are applying for (PhD project 1, 2, 3 or 4).

Applications must include: 
  • application (letter of motivation)
  • CV
  • documentation of a relevant completed M.Sc. or M.Eng.-degree
  • course and grade list of bachelor and master degrees
  • Excel sheet with translation of grades to the Danish grading system (see guidelines and excel spreadsheet here)
  • Example written English technical text (or a link to such a publication)
  • A link to an archive with software source code, if relevant
  • Please specify which PhD projects you are applying for.
Candidates may apply prior to ob­tai­ning their master's degree, but cannot begin before having received it.

All interested candidates irrespective of age, gender, race, disability, religion or ethnic background are encouraged to apply.  

DTU Compute has a total staff of 400 including 100 faculty members and 130 Ph.D. students. We offer introductory courses in mathematics, statistics, and computer science to all engineering programmes at DTU and specialised courses to the mathematics, computer science, and other programmes. We offer continuing education courses and scientific advice within our research disciplines, and provide a portfolio of innovation activities for students and employees.

DTU is a technical university providing internationally leading research, education, innovation and scientific advice. Our staff of 5,800 advance science and technology to create innovative solutions that meet the demands of society; and our 10,600 students are being educated to address the technological challenges of the future. DTU is an independent academic university collaborating globally with business, industry, government, and public agencies.

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